Triple
T3024186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conscience (Piers Plowman) |
E82537
|
entity |
| Predicate | literaryWorkLanguage |
P17914
|
FINISHED |
| Object | Middle English |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Middle English | Statement: [Conscience (Piers Plowman), literaryWorkLanguage, Middle English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryWorkLanguage Context triple: [Conscience (Piers Plowman), literaryWorkLanguage, Middle English]
-
A.
languageOfWritings
chosen
Indicates that a specified language is the one in which certain writings or written works are composed.
-
B.
languageOfParentWork
Indicates that the specified language is the language in which the parent (original or containing) work is expressed.
-
C.
languageOfBooks
Indicates the language in which the referenced books are written or published.
-
D.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
E.
literaryLanguage
Indicates that an entity is expressed, written, or communicated using a particular literary or standardized written language.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ad8b1fb34081908c1b873e2b7273e1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9abac0288190a30b42674eea501f |
completed | March 8, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69ad961c430c8190ac48f2e3c7e7c649 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3 p.m.